-
Notifications
You must be signed in to change notification settings - Fork 24
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Relation Prediction produces error after process 23%, with low rate of label2 #12
Comments
|
I'm also getting a similar performance. Early stopping is usually used during the training process, however, here we are using a pre-trained model during relation prediction (after the model has been trained), why is there an early stopping? Can you please elaborate on the 1) point? |
We did not implement any early stoppings during training. If you see some scenarios are not being used for training, this is probably because they are filtered by some logic in the data loader. You can search for 'return None' at the function For example, one of those filters is the agent_type filter. This means if you pass 'vehicle' in the 'agent_type' in the training command, all scenarios that have no vehicles marked to predict will be skipped. And this gets more complicated if you are training for conditional trajectory predictor. Here the loaded relation pickle has only a relation of v2v which requires both two agents to predict to be vehicles. If these conditions are not met, the scenario will be skipped. |
Thanks for the clarification. |
As graph, the Relation Prediction part produces errors after 23%. And the rate of Label2 at the moment is fairly low. On the one hand, I can't see the reason why it's popping out. On the other hand, it is quite strange for the Label2 rate since it is only a prediction. Does this ever happen to you guys?
The text was updated successfully, but these errors were encountered: